估计员
数学
应用数学
筛子(范畴论)
参数统计
非参数统计
多项式的
一致性(知识库)
数学优化
统计
离散数学
数学分析
作者
Xuewen Lu,Yan Wang,Dipankar Bandyopadhyay,Giorgos Bakoyannis
出处
期刊:Statistica Sinica
[Statistica Sinica (Institute of Statistical Science)]
日期:2023-01-01
标识
DOI:10.5705/ss.202021.0051
摘要
In this paper, we consider a class of partially linear transformation models with interval-censored competing risks data. Under a semiparametric generalized odds rate specification for the cause-specific cumulative incidence function, we obtain optimal estimators of the large number of parametric and nonparametric model components via maximizing the likelihood function over a joint B-spline and Bernstein polynomial spanned sieve space. Our specification considers a relatively simpler finite-dimensional parameter space, approximating the infinite-dimensional parameter space as n → ∞, thereby allowing us to study the almost sure consistency, and rate of convergence for all parameters, and the asymptotic distributions and efficiency of the finite-dimensional components. We study the finite sample performance of our method through simulation studies under a variety of scenarios. Furthermore, we illustrate our methodology via application to a dataset on HIV-infected individuals from sub-Saharan Africa.
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